A similarity model for bibliographic records using subject headings

We propose a model for measuring similarity between bibliographic records based on their keywords or subject headings whose relationship can be represented in form of the semantic hierarchical network. In our work, the level of each subject heading in the semantic hierarchical network plays a major role to determine keyword´s infuence. Highly specifc subject headings represented as leaf nodes of the model are better indicators to explain the content of a bibliographic record than the more general ones. The proposed algorithm calculates the level of similarity between records by considering path from one subject heading to another contained in the records. With this algorithm, related bibliographic records do not necessary to have exactly the same subject heading. The implication of this work can be applied to various types of document classifcation whose set of tags or keywords are organized in a semantic hierarchical network.